maedeh mosayeb motlagh; Parham Azimi; maghsoud Amiri
Abstract
This paper investigates unreliable multi-product assembly lines with mixed (serial-parallel) layout model in which machines failures and repairing probabilities are considered. The aim of this study is to develop a multi-objective mathematical model consisting the maximization of the throughput rate ...
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This paper investigates unreliable multi-product assembly lines with mixed (serial-parallel) layout model in which machines failures and repairing probabilities are considered. The aim of this study is to develop a multi-objective mathematical model consisting the maximization of the throughput rate of the system and the minimization of the total cost of reducing mean processing times and the total buffer capacities with respect to the optimal values of the mean processing time of each product in each workstation and the buffer capacity between workstations. For this purpose, in order to configure the structure of the mathematical model, Simulation, Design of Experiments and Response Surface Methodology are used and to solve it, the meta-heuristic algorithms including Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and Non-Dominated Ranked Genetic Algorithm (NRGA) are implemented. The validity of the multi-objective mathematical model and the application of the proposed methodology for solving the model is examined on a case study. Finally, the performance of the algorithms used in this study is evaluated. The results show that the proposed multi-objective mathematical model is valid for optimizing unreliable production lines and has the ability to achieve optimal (near optimal) solutions in other similar problems with larger scale and more complexity.IntroductionA production line consists of a sequence of workstations, in each of which parts are processed by machines. In this setup, each workstation includes a number of similar or dissimilar parallel machines, and a buffer is placed between any two consecutive workstations. In production lines, the buffer capacity and processing time of machinery have a significant impact on the system's performance. The presence of buffers helps the system to maintain production despite possible conditions or accidents, such as machinery failure or changes in processing time. Previous research has investigated production lines without any possibility of machinery failure, referred to as "safe production lines." However, in real production lines, machinery failure is inevitable. Therefore, several studies have focused on "uncertain production lines,"assuming the existence of a probability of failure in a deterministic or exponential distribution. This research examines uncertain production lines with a combined layout, resulting from the combination of parallel deployment of machines within each workstation, if necessary, and serial deployment of workstations. The objective of this research is to determine the optimal values (or values close to optimal) of the average processing time of each product in each workstation, as well as the volume of buffers, as decision variables. The approach aims to maximize the system's output while minimizing the costs associated with reducing the processing time of workstations and minimizing the total volume of buffers between stations. Moreover, simulation can be applied without interrupting the production line or consuming significant resources. In this research, due to the high cost and time involved, implementing the proposed changes on the system is not cost-effective for investigating the changes in the production system's output rate. Therefore, the simulation technique has been utilized to optimize the production line.Research methodThe present study aims to develop a multi-objective mathematical model, based on simulation, to optimize multi-product production lines. In the first step, the structure of the multi-objective mathematical model is defined, along with the basic assumptions. To adopt a realistic approach in the model structure, the simulation technique has been employed to address the first objective function, which is maximizing the output rate of the production line. To achieve this, the desired production system is simulated. The design of experiments is used to generate scenarios for implementation in the simulated model, and the response surface methodology is utilized to analyze the relationship between the input variables (such as the average processing time of each product type in each workstation and the buffer volume between stations) and the response variable (production rate).ResultsTo implement the proposed methodology based on the designed multi-objective programming model, a case study of a three-product production line with 9 workstations and 8 buffers was conducted. Subsequently, to compare the performance of the optimization algorithms, five indicators were used: distance from the ideal solution, maximum dispersion, access rate, spacing, and time. For this purpose, 30 random problems, similar to the mathematical model of the case study, were generated and solved. Based on the results obtained, both algorithms exhibited similar performance in all indices, except for the maximum dispersion index.ConclusionsIn this article, the structure of a multi-objective mathematical model was sought in uncertain multi-product production lines with the combined arrangement of machines in series-parallel (parallel installation of machines in workstations if needed and installation of workstations in series). The objective was to determine the optimal values of the average processing time of each type of product in each workstation and the buffer volume of each station, with the goals of maximizing the production rate, minimizing the costs resulting from reducing the processing time, and the total volume of inter-station buffers simultaneously. To investigate the changes in the output rate of the production system, due to the high cost and time, it was deemed not cost-effective to implement the proposed changes on the system. Therefore, the combination of simulation techniques, design of experiments, and response surface methodology was used to fit the relevant metamodel. In the proposed approach of this research, taking a realistic view of production line modeling, the probability of machinery failure, as well as the possibility of repairability and return to the system, were considered in the form of statistical distribution functions. Additionally, all time parameters, including the arrival time between the parts, the start-up time of all the machines, the processing time, the time between two failures, and the repair time of the machines, were non-deterministic and subject to statistical distributions. Finally, to solve the structured mathematical model, two meta-heuristic algorithms (NSGA-II) and (NRGA) were considered.
supply chain management
fateme khanzadi; Reza Radfar; nazanini pilevari salmasi
Abstract
Nowdays, supply chain specialists are looking for the integrated development of the supply chain model in order to increase the competitiveness, effectiveness and reduce the problems in the supply chain. They always seek to identify and develop this process so that they can cover more aspects of the ...
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Nowdays, supply chain specialists are looking for the integrated development of the supply chain model in order to increase the competitiveness, effectiveness and reduce the problems in the supply chain. They always seek to identify and develop this process so that they can cover more aspects of the chain. Adding effectiveness indicators along with LARG indicators and using the basics of the dynamic system to improve the efficiency of the supply chain is one of the innovations of this study. At first, by using research literature and studies, 12 headings of indicators were selected as LARG-E indicators. Then, with the Fuzzy Delphi method, the relationships and importance of each of these components were determined, and more important variables were modeled for further investigation. With using the concepts of dynamic systems, causal loops were drawn. Then, to check the function of the model, dynamic hypotheses were developed with the opinion of experts. In the next step, the flow diagram of the model and also the validation tests of the proposed model were done. Finally, by examining the outputs obtained from the proposed scenarios, it was found that most of variables have better behavior in LARG-E approach.IntroductionIn recent years, with the addition of various competitions in the world markets, many researches have been conducted to use new technologies and researches in order to improve the production process and increase the effectiveness of these competitions as much as possible (Mohghar et al., 2017). All the goals that work in this field increase the competitiveness of the organization. This competition is by reducing costs, being present in the market and satisfying the customer. To increase profits, protect the environment, keep the markets stable and meet the expectations of customers, organizations should be provided using the existing environments in a set of customers (Pisha et al., 2016). Use chain management requires the use of new facilities and improvements to previous findings such as lean, agile, resilience and green to increase speed and competitiveness, selection and decision-making to achieve the organization and maximum effectiveness.Today, supply chain specialists are looking for the integrated development of the supply chain model to increase the effectiveness and efficiency of the supply chain in order to increase competitiveness and reduce supply chain problems. In this case, there is a consensus among experts that there is no comprehensive model. All the mentioned cases make it inevitable to design a comprehensive and effective model for the supply chain. The verifiable issue is the conflicts and the non-alignment of all the indicators of the paradigms with each other. LARG paradigms, without considering the spirit of effectiveness in each supply chain, cannot fully protect it against continuous changes in the competitive market arena. A comprehensive model that pays particular attention to effectiveness while implementing LARG paradigms has not been examined in the literature review and the consensus of experts. Therefore, in this research, we are looking to design a comprehensive model in a LARG-effective manner so that the effect of various LARG-effective indicators on the performance of the supply chain can be investigated. The integration of LARG paradigms has been studied a lot so far, but its development is based on the concepts of innovation effectiveness of this research, and in this way, the dynamic system approach was used.Materials and MethodsTo formulate a LARG supply chain, first the framework, indicators and variables of each LARG paradigm were extracted from the research literature, then in order to develop them with effective concepts, the effective supply chain was studied. In order to implement the fuzzy Delphi approach, based on the effectiveness indicators extracted from the subject literature and LARG supply chain approaches, operational indicators were provided to the experts participating in the research in the form of a questionnaire via email and after initial coordination. After collecting the completed questionnaires, fuzzification operations, fuzzy averaging and then de-fuzzification were performed. The results were brought to the attention of the participants and they were asked to apply their desired changes according to the obtained results. This approach reached the saturation stage in the third round and there was no change in the opinions of the participants and the consensus of the panel experts was the final and trusted output of the Delphi method. Finally, according to these weights, 9 quantitative variables had the highest importance and were used for dynamic modeling. The simulation stage is done with the help of software and Nasim. According to the features of modeling based on system dynamics, this approach was chosen as the main research tool in this study because there are linear relationships between the variables and there are nested feedbacks between the variables of the subsystems, the importance of simultaneously improving the performance in different layers of the producer, supplier and distributor. Which is one of the goals of this research, with this approach, it can be a very suitable tool for decision-making by the senior managers of the organization.Discussion and ResultsOrganizations are trying to improve their competitiveness by adopting Lean, Resilient, Green and Agile strategies; But as it was said, the implementation of these paradigms, which sometimes have conflicting results, requires a new integration and index to align the goals. So far, many researches have been done by merging two or more paradigms, the combination of all 4 paradigms called LARG has greatly helped to improve the performance of supply chains, but in this research, in order to improve the conflicts between paradigms, a new concept of spiritual effectiveness was given to the supply chain. Understanding the dynamics of applying the above four strategies and their effectiveness was done using the dynamic systems approach. In this research, the indicators of the LARG supply chain were defined based on theoretical foundations and interviews with experts; then the effectiveness indicators were placed next to them. These indicators were implemented in the printing and ink industry. In this way, an effective LARG integrated system was defined; then, using a dynamic model, dynamic hypotheses were first defined and state and flow diagrams were drawn. After correctness of the model and validation of the model, two scenarios were examined for 8 important variables. After applying the scenarios, the performance of LARG and effective LARG was compared. By applying each scenario in the designed model, it was possible to check the effect of new indicators on the variables and their behavior.ConclusionsAs a result, if the components of the effective supply chain are properly integrated with the LARG concepts, they integrate the conflict that may exist between the LARG paradigms and play the role of synchronization and improvement as a ruler and standard. The effective management of the LARG supply chain may not be defined as an independent variable, but it is a result of variables and indicators that improved performance in most cases.
SEYYED ALI Mirnezhad; Parham Azimi; Ahmad Yousefi Hanoomarvar
Abstract
In the present study, the redundancy allocation problem (RAP) of series-parallel system has been investigated to maximize the system's availability. To achieve the research objective, budget, weight and volume constraints, and the maximum and minimum number of elements assigned to each subsystem have ...
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In the present study, the redundancy allocation problem (RAP) of series-parallel system has been investigated to maximize the system's availability. To achieve the research objective, budget, weight and volume constraints, and the maximum and minimum number of elements assigned to each subsystem have been considered. The main innovation of this research is to consider the failure and repair rates of components with non-exponential distribution function in the process of optimization. Taking into account failure and repair rate via non-exponential distribution function makes it impossible to calculate accessibility using mathematical relations. Therefore, the present study has used simulation method to calculate system availability. Since the simulation has no optimization capability On the other hand, in the redundancy allocation problem, it is necessary to evaluate the system availability recurrently in order to find the optimal solution. Further, due to the high degree of difficulty of developed mathematical function, the genetic metaheuristic algorithm was used to solve it. Finally, the efficiency of the genetic algorithm was measured against particle swarm algorithm and simulated annealing algorithm. To compare fairly, the parameters affecting the algorithms are adjusted using the Taguchi method and the algorithms are in their best practice. The computational results prove the high ability of the genetic algorithm in optimizing the concerned problem.
Ebrahim Alimohammadi As; Alireza Bafandeh Zendeh; Houshang Taghizadeh
Abstract
The study aims to simulate the strategies of Islamic Azad University (Tabriz branch) during 2019- 2034 period through system dynamics approach. Based on research literature, student trend, physical resources, educational quality, human resources, research and publication and financial operation were ...
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The study aims to simulate the strategies of Islamic Azad University (Tabriz branch) during 2019- 2034 period through system dynamics approach. Based on research literature, student trend, physical resources, educational quality, human resources, research and publication and financial operation were considered as key effective variables in formulating the strategies. By using reliable theories in the field of problem-solving literature and experts' opinion, causal relations between variables have defined in the form of mathematical functions and finally simulated has been done. The scenarios were formulated and analyzed based on three main objectives, namely cost reduction, increase of revenue and educational quality development. Results show that by the implementation of downsizing scenario in Tabriz Azad University, the tuition rate of the university experienced a decrease of five percent. The second scenario show that if research budget experiences a change of 40%, non-fee revenues would grow 19%. The simulation of the third scenario revealed that, 25% increment of new investments in Tabriz Azad University leads to the growth of student attraction rate by 17% in long term. By considering results of three scenarios we could suggest that Tabriz Azad University should follow the two strategies of increasing research budget and making use of new investments.
Shamsoldin Hosseini; Parham Azimi; Mani Sharifi; Mostafa Zandieh
Abstract
The aim of dynamic facility layout problem is to find the best layout for facilities at a multi period planning horizon so that the total cost of material handling and relocating the facilities is minimized. This paper developed a bi-objective mathematical model which is able to simultaneously minimize ...
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The aim of dynamic facility layout problem is to find the best layout for facilities at a multi period planning horizon so that the total cost of material handling and relocating the facilities is minimized. This paper developed a bi-objective mathematical model which is able to simultaneously minimize the material handling costs between facilities and the cost of rearrangement facilities and material handling time. Due to probabilistic characteristic of the transporters, such as the time of handling operation and existence of the failure, calculating the time required to carry the material using analytical relationships is impossible.Therefore, this paper uses the simulation approach and artificial neural networks. In this approach, a lot of scenarios are generated by combining of various levels of variables. Each scenario shows the location of the facilities and how transportation operations in each period is performed. Then each of these scenarios is implemented through computer simulation and simulation results are considered as the response variable. Finally, using input and response variable, an artificial neural network is trained to accurately estimate the time of carrying out the transportation operations. Given that the above problem is a NP-hard; this paper proposes a new meta-heuristic algorithm to optimize the problem and compares the performance of the proposed algorithm with existing algorithms in literature.
Nastaran Bakhshizadeh; Parham Azimi
Abstract
In nowadays market, the increased level of competitiveness and uneven fall of the product/service demands are pushing enterprises to make key efforts for optimization of their process management. It involves collaboration in multiple dimensions including information sharing, capacity planning, and reliability ...
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In nowadays market, the increased level of competitiveness and uneven fall of the product/service demands are pushing enterprises to make key efforts for optimization of their process management. It involves collaboration in multiple dimensions including information sharing, capacity planning, and reliability among players. One of the most important dimensions of the supply chain network is to determine its optimal operating conditions incurring minimum total costs. However, this is even a tough job due to the complexities inherit the dynamic interaction among multiple facilities and locations. In order to resolve these complexities and to identify the optimal operating conditions, we have proposed a hybrid approach via integrating the simulation technique, Taguchi method, robust multiple non-linear regression analysis and the Harmony Search algorithm, which is the main contribution of the research. In the first experiment, design concepts are used to define a number of scenarios for the supply chain. Then each of these scenarios is implemented in a simulated environment. The results of the simulation used to estimate the relationship between the chain and chain cost factors. This relationship can be used to optimize the supply chain which minimizes the system costs. This research provides a framework to understand the intricacies of the dynamics and interdependency among the various factors involved in the supply chain. It provides guidelines to the manufacturers for the selection of appropriate plant capacity and proposes a justified strategy for delayed differentiation.
Mohammad saeed Company; Parham Azimi
Abstract
In this study, the use of simulation technique in bi-objective optimization of assembly line balancing problem has been studied. The aim of this paper is to determine optimal allocation of human resource and equipment to parallel workstations in order to minimize the cost of adding equipment and manpower ...
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In this study, the use of simulation technique in bi-objective optimization of assembly line balancing problem has been studied. The aim of this paper is to determine optimal allocation of human resource and equipment to parallel workstations in order to minimize the cost of adding equipment and manpower among the stations and maximize the production output. In other words, with optimal use of resources, production output is maximized and therefore productivity become maximum. To this end, with optimization via simulation, the production line process is simulated in the form of a simulation model in the ED software. After validating the simulation model using design of experiment, various scenarios designed and run in the simulation model. Possible results for human resource and equipment variables, obtained by genetic algorithm are shown in a Pareto chart and have compared with the production line current situation
Parham Azimi; Farhad Hadinejad
Abstract
Reliability optimization and mean time to failure are those of the areas of interest for engineers and designers of systems and the use of redundancy components is one of the most common approaches in this field. The purpose of the optimization problem, finding the optimum number of redundancy components ...
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Reliability optimization and mean time to failure are those of the areas of interest for engineers and designers of systems and the use of redundancy components is one of the most common approaches in this field. The purpose of the optimization problem, finding the optimum number of redundancy components that must be satisfied the objectives of reliability engineering in the system. But usually the reliability improves results in increased costs and changes in parameters such as volume and weight of the system; therefore, it is necessary to establish a balance between resources. In previous researches, redundancy allocation problem is studied with non-repairable components or failure rate with exponential distribution; but in this study, repairable components and rates of failure and repair a non-exponential distribution assumed. Thus the purpose of this paper is solving reliability redundancy allocation problem with the goals of increasing the mean time to failure, reduce costs and reduce the variance of the shelf life of the system, while taking into account constraints such as volume and weight of the system. To this end, the research effort will be using mathematical and statistical techniques such as multi criteria decision making models, design of experiments, simulations, and computer software associated with them, provide a new approach for solving reliability redundancy allocation problem in series-parallel systems with repairable components
Parham Azimi,; Mohammad Reza ghanbari,*
Volume 13, Issue 38 , October 2015, , Pages 133-161
Abstract
Considering the increasing demand for operational activities in ports, ports managers are facing the challenge of optimal usage of port facilities and equipment. (In the last two decades, maritime transportation systems have been experienced an increasing development. Now the rate of development in this ...
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Considering the increasing demand for operational activities in ports, ports managers are facing the challenge of optimal usage of port facilities and equipment. (In the last two decades, maritime transportation systems have been experienced an increasing development. Now the rate of development in this section has been reached 8 percent per year. Nowadays, the port managers are faced with the challenge of optimal use of equipment and facilities). One of these challenges is to reduce the waiting times of ships at the ports.so that in this study, placing the buffer area for loading and unloading cereals has been investigated using a simulation optimization model based on queuing theory at SHAHID RAJAEE port. Three important criteria of the port performance have been considered including the ship turn-around time, number of loaded ships and loading norm. The results indicate that optimization of cereal transportation between the buffer area and the port can increase the capacity of transportation and loading- unloading capacity up to (The results show that the proposed model can increase the capacity of loading and unloading of the system up to %15.5between the port and buffer area.)
Ali Mohtashami*
Volume 12, Issue 33 , July 2015, , Pages 97-124
Abstract
This paper presents a multi-objective mathematical model for redundancy allocation in production systems. In many of the production and assembly lines, process times, time between failures and repaired times are generally distributed. The proposed method of this paper is able to consider time dependent ...
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This paper presents a multi-objective mathematical model for redundancy allocation in production systems. In many of the production and assembly lines, process times, time between failures and repaired times are generally distributed. The proposed method of this paper is able to consider time dependent parameters as general distribution functions by using the hybrid approach of simulation and response surface methodology. The objectives of the mathematical model are maximizing production rate, minimizing total cost and maximizing quality. In order to solve the proposed mathematical model, non-dominated sorting genetic algorithm and multiple objective particle swarm optimization are used. Numerical results indicate the effectiveness of both algorithms for generating non-dominated solutions. Moreover, comparative results indicate the superiority of the Non-dominated sorting genetic algorithm.
